Training data are crucial for advancements in artificial intelligence, but many questions remain regarding the provenance of training datasets, license enforcement and creator consent. Mahari et al. provide a set of tools for tracing, documenting and sharing AI training data and highlight the importance for developers to engage with metadata of datasets.
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N.V. has contributed to separate streams of research for companies that produce LLMs and LLM-based applications, including Microsoft and OpenAI. This article was not supported by any institution other than the author’s home university, Simon Fraser University.
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Vincent, N. A step forward in tracing and documenting dataset provenance. Nat Mach Intell 6, 848–849 (2024). https://doi.org/10.1038/s42256-024-00884-w
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DOI: https://doi.org/10.1038/s42256-024-00884-w
